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--- |
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license: llama3 |
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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: MedQA_L3_1000steps_1e7rate_SFT |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# MedQA_L3_1000steps_1e7rate_SFT |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7486 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-07 |
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- train_batch_size: 2 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.774 | 0.0489 | 50 | 1.7867 | |
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| 1.7099 | 0.0977 | 100 | 1.6989 | |
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| 1.5873 | 0.1466 | 150 | 1.5668 | |
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| 1.4721 | 0.1954 | 200 | 1.4501 | |
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| 1.3469 | 0.2443 | 250 | 1.3336 | |
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| 1.2381 | 0.2931 | 300 | 1.2152 | |
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| 1.1195 | 0.3420 | 350 | 1.1046 | |
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| 1.0094 | 0.3908 | 400 | 1.0086 | |
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| 0.9372 | 0.4397 | 450 | 0.9280 | |
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| 0.8756 | 0.4885 | 500 | 0.8669 | |
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| 0.8221 | 0.5374 | 550 | 0.8219 | |
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| 0.8048 | 0.5862 | 600 | 0.7900 | |
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| 0.7759 | 0.6351 | 650 | 0.7691 | |
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| 0.7465 | 0.6839 | 700 | 0.7568 | |
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| 0.7426 | 0.7328 | 750 | 0.7506 | |
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| 0.7462 | 0.7816 | 800 | 0.7488 | |
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| 0.7764 | 0.8305 | 850 | 0.7486 | |
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| 0.7327 | 0.8793 | 900 | 0.7486 | |
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| 0.7316 | 0.9282 | 950 | 0.7486 | |
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| 0.7478 | 0.9770 | 1000 | 0.7486 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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